Implementation Issues
Many simulation codes may be formulated naturally as stencil codes. Since computing time and memory consumption grow linearly with the number of array elements, parallel implementations of stencil codes are of paramount importance to research. This is challenging since the computations are tightly coupled (because of the cell updates depending on neighboring cells) and most stencil codes are memory bound (i.e. the ratio of memory accesses and calculations is high). Virtually all current parallel architectures have been explored for executing stencil codes efficiently; at the moment GPGPUs have proven to be most efficient.
Read more about this topic: Stencil Codes
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